Attributes of Effective Communication

1. How to Engage Your Audience and Keep Them with You
https://www.hamilton.edu/oralcommunication/how-to-engage-your-audience-and-keep-them-with-you

2. 5 steps to find and engage your target audience
http://www.imediaconnection.com/content/33301.asp

3. Marketing:
relate
laugh
remember

4. Ramit Sethi on Persuasion and Turning a Blog Into a Multi-Million-Dollar Business
http://fourhourworkweek.com/2014/10/09/ramit-sethi-on-persuasion-and-turning-a-blog-into-a-multi-million-dollar-business/

5. YouTube Charisma On Command: http://bit.ly/subscribeCOC
@CharlieHoupert
on Persuasion
How to become a better leader

If you're interested in other videos that cover the topic of influence, but in a more social context, check out Ricky Martin on the Voice: https://www.youtube.com/watch?v=dqragS38hCk

5.1. 
5 Steps to Influence Like Barack Obama
https://www.youtube.com/watch?v=H3aWbte8DxU&t=600s

Watch President Obama address deadly Oregon Shooting

1. Introduce the problem you have. What's getting done is not enough. Associate pain with the status quo.

2. Preemptively handling objections. Handling objections before people bring them up. 6-7 objections. 3/4 of the speech. If objections are not handled preemptively, people dig in into their positions expressing objections,

3. Convince of Consistency: The change you want to people to make is consistent with their beliefs. Make people to feel that it is a part of their identity. Give them implicit personal ownership of the change. Take pre-existing action and show how it's the beginning of the change he wants people to do.

4. Picture how things will be when the change is implemented. Give details (Obama skipped).

5. Ask for help. Because you can't make things yourself.

5.2. Eye contact secrets

The secret of Bill Clinton's Charisma

https://www.youtube.com/watch?v=0o_EK4EjuEY

1. Let a person to feel that you are focused on him. When answering a question, 90-95% of time looking directly at a person.
A person would say that when he spoke with Bill Clinton, he felt like the only person in the room.
2. Narrow shape of eyes during eye contact - makes eye contact serious and intense.

3. Signal with your body language that you are about to leave. This way ending the eye contact doesn't seem sudden. 

5.3. How To Influence People With Your Word Choice
https://www.youtube.com/watch?v=dqragS38hCk

Steve Jobs' Leadership breakdown

1. Starts with the clear, achievable and persuasive vision. Core beleive: People with passion can change the world. Keep and re-iterate the vision. One step closer - the goal is there. It's not a mirage. 

Marketing message must be very simple, one sentence. 

Example: iPod - 1000 songs in  your pocket. First computer - Bicycle for the mind

2. Refocusing on the vision. Make people feel that everything is possible. Emotionally charged, High stakes metaphors fired people up (mortal enemy, war, survival, battles). Emotional engagement. People feel they need to win a battle.

3. Steve Jobs believed everything he was saying. It's in the choice of words. Certainty, not a possibility. Not we can, we will do this. To communicate certainty with the tone of your voice and micro-expressions you must be confident.

5.4. Bruce Lee's Insane Charisma
https://www.youtube.com/watch?v=Moc1Ur7X3dE

1. Charismatic person controls frame. In any question there is a frame. Charismatic person changes a frame of the questions to be more interesting, to allow people to connect etc. Takes opportunity to share his philosophy. Charismatic person values self expression over brevity.

2. Rejecting the form of the question. Expresses his beliefs.
Brake the frame if it conflicts with your feelings.



5.5. Be Instantly Magnetic
https://www.youtube.com/watch?v=RRjRgT8QQ3c
3 Jokes That Make People Instantly Like You

Ellen Degeneres' Tips To Making People Instantly Like You
Discover The 4 Emotions You Need To Make a Killer First Impression:
https://goo.gl/Ckpmhe

1. Ellen's jokes don't hurt anyone.

2. She makes herself the butt of her jokes comparing herself to other people. Classic self-deprecating humor.

3. The subtext of a joke is exactly the opposite of the text.
Poking fun. Context matters. People are not getting upset when the joke is about something temporary, common, not a core to their identity.

4. Gold standard of the joke - Ego boosters. People will immediately like you.


5.6. I am the greatest
Muhammad Ali's secret to insane confidence
https://www.youtube.com/watch?v=EsXU9UC-3Xg

5.7. The 5 Charismatic Habits Of The Rock (Dwayne Johnson)https://www.youtube.com/watch?v=walnCp3Qfcg

5.8. Jennifer Lawrence Charisma Breakdown - Funny, Self-Deprecating Stories

Get the 4 emotions you need to make a great first impression every time: 
https://goo.gl/ek2V13

https://www.youtube.com/watch?v=btud-zsdmk4

5.9. Why Trump Will SMASH Hillary

https://www.youtube.com/watch?v=LibRNYJmZ-I

Published on May 23, 2016

5.10. Donald Trump's Debates: 5 Mental Tricks You Didn't Notice
https://www.youtube.com/watch?v=9LR6EA91zLo
6. Scott Adams on persuasions

6.1. Dilbert Creator Scott Adams on Predicting Trump Winning in a Landslide

Published on Nov 7, 2016
https://www.youtube.com/watch?v=c-sBO6OppAc
6.2. Trump’s Tactics and Hillary’s Persuasion Game (Scott Adams Interview)
https://www.youtube.com/watch?v=I3BQGwESVbU

6.3. Scott Adams on The Persuasive Ways of Donald Trump (from Joe Rogan Experience #874)
https://www.youtube.com/watch?v=JK1eUSvxJSQ

6.4. Scott Adams of Dilbert on Trump's Genius
https://www.youtube.com/watch?v=uERs7AyaQmA

etc.
https://www.youtube.com/results?search_query=scott+adams+trump

The persuasion tactics Trump and Clinton are using to manipulate voters
By Kyle Smith
September 10, 2016
http://nypost.com/2016/09/10/the-persuasion-tactics-trump-and-clinton-are-using-to-manipulate-voters/

Donald Trump’s speaking bears the stamp of Cialdini’s techniques, which Barack Obama is rumored to have used on his path to the White House and which Hillary Clinton might also be studying. (Asked by the Financial Times whether he was advising Clinton, Cialdini took a “longish pause” and answered, “It’s my policy not to speak about any campaign that’s ongoing. The emotions are too deep.”)


Other election predictions





Published on Jul 1, 2016


How Trump will win election, and beat Hillary bad. Going through the interactive electoral map.

https://www.youtube.com/watch?v=vre23d-H_N8

I WAS RIGHT! This is the more accurate way to predict now - its better than polls because the pollsters are now paid for.

RESEARCH ON POLITICAL RHETORIC

1. Social Identity, Political Speech, and Electoral Competition

http://www.nyu.edu/gsas/dept/politics/faculty/dickson/dickson_politicalspeech.pdf

Social Identity, Political Speech, and Electoral Competition Eric S. Dickson New York University Kenneth Scheve University of Michigan∗ April 13, 2005 Key words: Elections, Ethnic Politics, Campaign Rhetoric, Valence Competition

2. Ivan Krastev -
https://www.ted.com/speakers/ivan_krastev
Marketing revolution -> Margaret Thatcher - Let the rich get richer
Internet revolution -> Echo Chambers, Political Ghettos
Brain Science revolution -> Don't talk about policies. Let me manipulate emotions.

3. Activist Politics and Art
http://jewishcurrents.org/
JFK
http://jewishcurrents.org/myth-jfk-22907



3. Marine Le Pen
Decoding Marine Le Pen's Rhetoric
A database and visualization research project

https://decodingmarinelepen.stanford.edu/

Stanford Report, April 16, 2015
Stanford scholar unpacks the rhetoric behind extremist politician's mainstream success

A pioneering textual analysis of French political speeches led by Stanford Professor of French Cécile Alduy reveals how Marine Le Pen, leader of France's surging far-right National Front, has made extremism palatable in a land of republican values.

BY BARBARA WILCOX
The Humanities at Stanford
An associate professor of French at Stanford, Alduy conducted a qualitative and quantitative analysis of more than 500 speeches by Marine Le Pen and her father, Jean-Marie Le Pen, to find out what has made their party surge in the polls.
http://news.stanford.edu/news/2015/april/extremism-france-alduy-041615.html

"Marine Le Pen's language is full of ambiguities, double meanings, silences and allusions," Alduy said.
This diagram shows the spatial lay out of Marine Le Pen's discursive universe. Using factorial analysis in Hyperbase, one can create a "map" of all the most used words and how they correlate to one another: the closer they are spatially, the stronger their correlation, or how often they appear together. Courtesy Ceceli Alduy












Why Trump Will SMASH Hillary
Charisma on Command
https://www.youtube.com/watch?v=LibRNYJmZ-I

NLP for Public Speaking and Debates

Virtual Audience
Augmented Political Intelligence
Rating Persuasion of Political/Public Communication
Persuasion Engine

Persuasion workflow:
OCEAN psychometric assessment to break audience into the 5 groups.
Deep customer segmentation.
addressing each group with customized persuasion.
Behavioral Microtargeting. Political Campaign Support.
Data-driven behavior change.

The Psychology of Persuasion
Robert Cialdini - Harnessing The Science Of Persuasion.pdf
http://content.yudu.com/Library/A17ln5/RobertCialdiniHarnes/resources/1.htm

Identify possibly six different patterns in persuasive TED talks.
http://changingminds.org/techniques/general/cialdini/cialdini.htm

Reciprocity: Obligation to repay. Consistency and Commitment: Need for personal alignment. Social Proof: The power of what others do. Liking: The obligations of friendship. Authority: We obey those in charge. Scarcity: We want what may not be available. if Social Proof - action words, positive sentiment pre-processing by parsing and extracting action verbs extract how strongly audience can relate to the story see also https://www.amazon.com/Pre-Suasion-Revolutionary-Way-Influence-Persuade/dp/1501109790/ref=pd_sbs_14_t_0 Pre-Suasion: A Revolutionary Way to Influence and Persuade September 6, 2016 by Robert Cialdini Ph.D. Identify five parts of the persuasive speech calling for an action (charisma on command, Charlie Houpert) 5 Steps to Influence https://www.youtube.com/watch?v=H3aWbte8DxU&t=600s 1. Introduce the problem you have. What's getting done is not enough. Associate pain with the status quo. 2. Preemptively handling objections. Handling objections before people bring them up. 6-7 objections. 3/4 of the speech. If objections are not handled preemptively, people dig in into their positions expressing objections, 3. Convince of Consistency: The change you want to people to make is consistent with their beliefs. Make people to feel that it is a part of their identity. Give them implicit personal ownership of the change. Take pre-existing action and show how it's the beginning of the change he wants people to do. 4. Picture how things will be when the change is implemented. Give details (Obama skipped). 5. Ask for help. Because you can't make things yourself. Virtual Audience (NLP) strategy feedback methodology: to use NLP feedback break down your strategy into specific purpose parts 1. input one part of your five part strategy 2. let NLP to score the entered part against the training set Strategics steps politician takes to win a competition ( Trump, see Charlie Houpert bet on Trump youtube video) 1. Get attention 2. Win one at a time 3. Remove threats one at a time 4. Define the terms of the engagement as though you are already a winner 5. Be flexible to attract only the people who follow you Mistakes politician makes to help his opponent (Hillary, see Charlie Houpert bet on Trump youtube video) 1. Be clever rather than impactful 2. Let others define the terms of engagement 3. Don't change your strategy 4. Just allow Donald to dismantle your weapons ******************************************** body language, facial expressions, voice modulation https://www.youtube.com/watch?v=IqsAhmTn7n4 Paul Ekman's facial expressions research - over 50 points, 7 basic emotions, over 3000 expressions, notice micro expressions. Create Dialog: questions and suggestions in response to a speech. Task - optimizing persuasion. http://arxiv.org/abs/1606.01269 End-to-end LSTM-based dialog control optimized with supervised and reinforcement learning Jason D. Williams, Geoffrey Zweig (Submitted on 3 Jun 2016) This paper presents a model for end-to-end learning of task-oriented dialog systems. The main component of the model is a recurrent neural network (an LSTM), which maps from raw dialog history directly to a distribution over system actions. The LSTM automatically infers a representation of dialog history, which relieves the system developer of much of the manual feature engineering of dialog state. In addition, the developer can provide software that expresses business rules and provides access to programmatic APIs, enabling the LSTM to take actions in the real world on behalf of the user. The LSTM can be optimized using supervised learning (SL), where a domain expert provides example dialogs which the LSTM should imitate; or using reinforcement learning (RL), where the system improves by interacting directly with end users. Experiments show that SL and RL are complementary: SL alone can derive a reasonable initial policy from a small number of training dialogs; and starting RL optimization with a policy trained with SL substantially accelerates the learning rate of RL.

Learn from Tad Devine - top media expert, chief strategist for Bernie Sanders.  Flawless public speech at WADR Bloomberg.

Argument: Politics and marketing - any public speech - is a technology. We can estimate the effect of the speech and improve it.
ref: Politics and Religion are technologies - TED talk by Noah Feldman
1. Providing Feedback based on the testing of a given text for desired effects

- Addressing different types of audience

- Pro-Government vs Libertarian

see Snowden

- Young Open Minded Technical Savvy

- Evangelicals what makes political speech to appeal to a specific population

- Persuasion, Openness, Intellectual Brilliance, and Leadership, etc.

Methodology: Comparison of two Contextual Mappings - the wordings in great speeches and tested texts.

-Using factorial analysis in Hyperbase. Graphical representation of the speech - spatial distribution - clouds - of words with smaller distances corresponding to higher frequencies of co-occurrences of the words.

-marketing - golden circle-Apple example in Simon Sinek 'How great leaders inspire action' TED talk

https://www.ted.com/talks/simon_sinek_how_great_leaders_inspire_action?language=en

recher vocabulary -> higher engagement

2. Stretch Goal - Recommending speech rewording by translating a given fragment to the one from a recognized high ranking speaker.

Technical details:

RNN with LSTM - translation, see
Ilya Sutskever's home page
www.cs.toronto.edu/~ilya
‎Publications - ‎RNN text generation demo - ‎Award

1. Collecting a corpora  - training set of the phrases/paragraphs rated by experts in a binary fashion as
 - persuasive/non-persuasive (convincing/unconvincing) (similar to positive/negative sentiment)
 - rhetorical quality (compare to great rhetoric in famous speeches)

Analysis -
sub-properties of "convincing":
self promotion  - verbal, explicit, implicit, tone, body language - posture, pose, gestures, facial expression
audience can relate to the key concepts
establishing trust
perceived openness
perceived leadership
perceived credibility
key position statements
key promises that are important to an audience
etc.

experts can rate the phrases or entire documents by subproperties. the resulting score can be used to validate a general conclusion on "convincing" property.

2. Building a model for scoring a phrase convincibility (persuasion).
3. Using ensemble model that includes RNN model.
4. Testing prepared speeches, answers to anticipated questions, political platform descriptions against strong persuasion model
5. Improving a corpora by updating it based on the real life results.

Proving the effectiveness of the RNN scoring:
scoring social media - Twitter - for positive and negative sentiment in responses to high score- and low-score speeches and debates

RESPONSE SIMULATION FOR ACHIEVING MAXIMUM RESONANCE

Creating a sandbox for adjusting the input message to receive desirable response

1. Collecting large amounts of feedback messages in response to the various political input speeches.
2. Visualizing the clusters of responses to each input speech
3. Simulating the response to the input speech based on the prior experiences.

This work lies in the intersection between the areas of computational creativity and information retrieval. In our approach, we assume that users have a certain concept in their mind, formulated as a sequence of lines, and their information need is to find the missing lines, composing a convincing sequence. Such an information need does not have a factual answer; nevertheless, users will be able to assess the relevance of the response provided by the system. The relevance of the response depends on factors that include expressive force, vocabulary, unexpectedness, semantic coherence, and humor. We use an open-source speech synthesizer, eSpeak, to produce the transcription. eSpeak has also text to-phonemes functionality.

eSpeak text to speech
http://espeak.sourceforge.net/
VISUALIZATION AUGMENTING HUMAN INTELLIGENCE

LAYERING ANALYTICAL VISUALIZATIONS

EXAMPLE:

Quid’s article-analyzing app can tell you many things — like why you lost the Senate race in Iowa
http://venturebeat.com/2014/11/27/quids-article-analyzing-software-is-amazing-it-can-even-tell-you-what-went-wrong-in-your-political-campaign/

Finding patterns of lie in a competitor's speech
elevated jargon use in fundamentally deceptive papers
http://news.stanford.edu/news/2015/november/fraud-science-papers-111615.html

*********************************************
Main SW components: web portal, secure gateway, API manager, backend app deployer, DB, operational analytics.

Business Marketing Model: Native ads that look like a content (see LinkedIn as an example)

Visual comparison graph augments cognitive perception of similarity and differentiation of texts.

Feature Set for Prediction Of Political Success

1. IQ
http://www.businessinsider.com/the-15-smartest-us-presidents-of-all-time-2015-3

2. Financial support
3. Economic interests of the majority of voters
4. Strength of legal support
5. Charisma
6. Debate skills
7. Leadership skills
8. Relatable image
9. Ability to convince audience. Tools: use concepts to which audience relates.
10. Discerning untruthfulness, intentional fact distortion in a competitor speeches, statements.

Everybody wants to maximize his interest. Find the person and a group whose interest maximization will maximize your interest. This is a multi-entity one-shot game.
Application of Image Recognition
power and confidence posture recognition for politicians
Flow Chart of an Adviser - Augmented Intelligence - can be created with
https://www.draw.io/

notes:
check if anything new in http://arxiv.org/pdf/1601.06733v3.pdf

Long Short-Term Memory-Networks for Machine Reading
Jianpeng Cheng, Li Dong, Mirella Lapata
(Submitted on 25 Jan 2016 (v1), last revised 1 Feb 2016 (this version, v3))

generative model example:
DopeLearning: A Computational Approach to Rap Lyrics Generation
18 May 2015
http://arxiv.org/pdf/1505.04771.pdf

IBM's Watson can sense sadness in your writing
The AI just got a big emotion-detecting upgrade.
http://www.engadget.com/2016/02/22/ibm-emotion-detection-upgrade/

Scott Adams' analysis of the Trump's strategy with the voters: similar to hypnosis - lead and pace.
Lead: express similar feelings as your audience, win their sympathy and trust
Pace: diverge in the direction you want to go and see your audience following you because you already won their sympathy.

Enhancing charisma, breakdowns from Charlie Houpert Trump Prediction. Facts beat feelings:
1. Don't memorise your speech word by word. Only 3-9 logical parts. And exact opening and closing of your speech.
2. Speak with ease and conviction
3. Sound like authority being specific with numbers and facts. Expertise enhances charisma. Sound credible.
4. Feel comfortable answering difficult questions
5. Conviction (rather than softer tone) and congruency (genuine smile and laughter rather than a forced one)
6. Create stronger emotional connection with the audience:
6.1 Images and stories you invoke connect you to others
6.2 Speaking in the third person "they" and calling people by their group names (African Americans, Latinos) distances you from those people
6.3 Speak in second person, meaning you - we need your talents, your skills...
6.4 Look into the camera dead on makes an impression that you speak directly with the audience

AI vs Human Intelligence -
The Rise of AI Makes Emotional Intelligence More Important

https://hbr.org/2017/02/the-rise-of-ai-makes-emotional-intelligence-more-important

by Megan Beck,
Barry Libert
FEBRUARY 15, 2017
The booming growth of machine learning and artificial intelligence (AI), like most transformational technologies, is both exciting and scary. It’s exciting to consider all the ways our lives may improve, from managing our calendars to making medical diagnoses, but it’s scary to consider the social and personal implications — and particularly the implications for our careers. As machine learning continues to grow, we all need to develop new skills in order to differentiate ourselves. But which ones?

It’s these human capabilities that will become more and more prized over the next decade. Skills like persuasion, social understanding, and empathy are going to become differentiators as artificial intelligence and machine learning take over our other tasks. Unfortunately, these human-oriented skills have generally been viewed as second priority in terms of training and education. We’ve all experienced the doctor, financial planner, or consultant who is more focused on his or her reports and data than on our unique situations and desires.

YOW! 2016 Eva Nahari - NLP: Something Old, Something New.
https://www.youtube.com/watch?v=InayOc_Dpyg
YOW! Conferences

Published on Mar 7, 2017

AI for Security Vulnerability and Adversarial Neural Cryptography

Cross Site Request Forgery
https://www.owasp.org/index.php/Cross-Site_Request_Forgery_(CSRF)

Learning to Protect Communications with Adversarial Neural Cryptography

https://arxiv.org/abs/1610.06918
Martín Abadi, David G. Andersen (Google Brain)
(Submitted on 21 Oct 2016)
We ask whether neural networks can learn to use secret keys to protect information from other neural networks. Specifically, we focus on ensuring confidentiality properties in a multiagent system, and we specify those properties in terms of an adversary. Thus, a system may consist of neural networks named Alice and Bob, and we aim to limit what a third neural network named Eve learns from eavesdropping on the communication between Alice and Bob. We do not prescribe specific cryptographic algorithms to these neural networks; instead, we train end-to-end, adversarially. We demonstrate that the neural networks can learn how to perform forms of encryption and decryption, and also how to apply these operations selectively in order to meet confidentiality goals.